2020 trends in cloud computing: The epicenter of cloud native architecture
The service oriented economy of cloud computing has all but solidified throughout the data ecosystem. It’s single-handedly responsible for the modern way vendors interact with organizations, organizations interact with their customers and organizations interact with one another.
Whether accessed via hosted solutions, multi-tenant SaaS models, or hybrid on-premise, public, or private clouds, this architecture is the most cost effective and efficient means of scaling—horizontally and vertically—to meet the modern demands of the heterogeneous computing environments with which organizations contend.
Cloud architecture is the means of decoupling the enterprise stack to meet the fluidity of use cases and demands upon organizations. More importantly, perhaps, it’s the most viable option for creating new ones.
“Part of the benefit of this new architecture is formerly, if you’re going to have customers continuing to use [different] systems and you want to introduce new functionality, you have to develop it in each of those code bases,” says Hyland CEO and President Bill Priemer. “Part of this microservices based architecture is removing it from that. Many customers would like to still keep using what they’re using, but they’d still like us to offer new functionality. We’ll be able to do that with the new [cloud service] strategy.”
The ingenuity for novel products, services and business models endowed by cloud computing extends from the realm of B2C to B2B. Its boons are predicated on mastery of this architecture’s essentials of cloud native approaches, containers, orchestration platforms, data fabrics and security.
Success in these areas ingrains the cloud as the epicenter of data management, customer interactions, and digital interactions in general.
Cloud Native Technologies
The monetary gains, vertical disruptions, and customer satisfaction elicited from cloud computing is typified via cloud native technologies. These technologies range from underpinning cloud data management tools such as cloud stores to consumer-facing applications popularized by organizations like Uber or Air BnB.
The Cloud Native Computing Foundation defines cloud native technologies as those that “empower organizations to build and run scalable applications in modern, dynamic environments such as public, private, and hybrid clouds.” These technologies support tools granting access to data on demand and, except in the case of the cloud’s cheap storage, warrant nominal costs unless used. Cloud-native capabilities involve:
- Containers: Containers are lightweight, highly scalable, portable receptacles that include all logic required to run applications. According to DH2i CEO Don Boxley, “Cloud native is a whole new class of applications, all container-based and microservices, which are essentially containers.”
- Microservices: Microservices are a modern way of running the different parts of an application as discreet services that are interfaced, so if one fails the others propagate for continued application functionality.
- Infrastructure as code: Infrastructure as code buttresses the decreased physical hardware minimizing cloud native costs. With infrastructure as code, “the configuration and the setup are part of the code and are part of your pipeline,” Hyland CTO Sam Babic explained.
Cloud Native Advantages
Cloud native tools and applications are revered for their celerity, which is difficult to match with non cloud native solutions. Practices like ELT can make data immediately available for consumption in cloud data stores.
Similarly, industry disruptions by Fintech or Insurtech companies are gaining market share from traditional on-premise incumbents at the speed of which the former can underwrite claims or extend coverage due to the use of public data sources, for example. Processes that once took weeks or months are now completed in hours with cloud native approaches, exemplifying the digital disruption.
“You think about those non-traditional competitors and the reason that folks are going that route, a lot of it has to do with the digital capabilities and having information immediately accessible, mobile, and having a digital experience,” says Rick Hiles, Hyland Financial Services and Insurance sales manager.
Cloud native technologies are not limited to digital disruptors. Utilizing them is a sure means of accelerating digital transformation and competing with organizations ‘born’ in the cloud.
Container Orchestration, Cloud Automation
Because of the efficacy of cloud native technologies, applications, and capabilities supporting cloud deployments, orchestrating containers and their microservices delivers tangible value to cloud-savvy organizations. Containers are automated by orchestration solutions such as Kubernetes.
This platform reinforces the mobility that makes containers an integral aspect of application development and deployment, since it enables data resources “to be very quickly stood up in the cloud in a manner of minutes using Kubernetes cloud automation technology,” Cambridge Semantics CTO Sean Martin observes.
These orchestration capabilities allow organizations to specify how they want their application to run—how many instances, where, high availability needs, and other germane factors. Kubernetes internalizes these requirements to effectively automate them with an inductive reasoning based on what’s needed to achieve defined outcomes.
“Orchestration gets us to this place where okay, let’s not think about the hardware; I want to tell an application to go do what I need it to do,” says Hyland DevOps Engineer Nathan Lowe. “So, you get into this world where I need to deploy a new application or a new version of an application. It’s very simple to do that if something knows about your hardware and you don’t have to think about it.”
The Data Fabric Architecture
Although containers, microservices, and infrastructure as code are critical facets of cloud architecture, the data fabric tenet is quietly emerging as one of its definitional traits. These fabrics holistically link together data assets via the cloud wherever they are: whether on-premises, at the Internet of Things’ edge, or in public, private, or hybrid clouds.
Data fabrics are one of the ways of accounting for what Forrester analyst Cheryl McKinnon termed the “extended enterprise”, in which organizations not only manage their internal data but also external sources pertaining to “partners, suppliers, contractors, customers, citizens, patients, our law firms, our design agencies, etc.”
Data fabrics are becoming increasingly pivotal for enabling organizations to find and utilize their own data in the multiplicity of places they’re populated throughout the decentralized data landscape.
“You have a lot of existing debt in infrastructure from both technology and data sources,” Martin acknowledges. “How do you now bring those online? Well, this emerging architecture is meant to guide you. There are virtualization companies, for example, that can assemble combinations of data potentially, data quality tools, data lakes, data warehouses, ETL tools, data catalogs. All of these players have a part.”
The cloud is influential for accessing these different instruments once proper integration, aggregation, and data discovery capabilities are available.
Although security concerns will almost certainly endure, the array of security mechanisms available for data in the cloud is difficult to exceed on premises.
According to Hyland Senior Solutions Engineer Steve Wyant, the seven layers of cloud security include policies, procedures and security awareness, the physical datacenter, perimeter defenses, internal networks, hosts, applications, and data layers. It’s difficult to outspend public cloud providers to fortify these layers; it may be even more arduous to find an organization’s data in those clouds were they somehow breached. Security best practices for fortifying cloud deployments involve:
- The Data Layer: The data layer is critical because it represents the innermost layer of protection for information assets. Common methods for buttressing security at this layer include masking or tokenization (in which data are obscured), Public Key Authentication, and encryption. Organizations should ideally encrypt data in transit and at rest via client side encryption, in which they (not cloud providers) have the keys.
- The Host Layer: Reinforcing security at the host layer requires protecting servers, which was traditionally done via signature based antiviral constructs. According to Paul Adkins, Director of Global Cloud Services at Hyland, “Today, getting around a signature based antivirus is fairly trivial. The new, next generation antivirus endpoint detection and response is more behavior based, comparing against an algorithm as opposed to a signature. So, it’s far more difficult to get past.”
- The Application Layer: Developments in application layer security are notable because they encompass a range of layers from applications to perimeters. Micro-segmentation approaches in which data transmissions are routed between applications with discreet software defined perimeters are gaining credence because they illustrate the characteristics of cloud deployments and containers. They’re fluid, quickly facilitated, and highly available for redundancy. Boxley referenced their relevance to contemporary architecture “in which data is created, distributed, and shared across multiple clouds, IoT and the like. Software defined perimeters eschew architectural shortcomings of Virtual Private Networks, such as transmitting data over third-party servers.”
Cloud computing’s greatest accomplishment is more than simply transforming the data management field from a product oriented to a service oriented economy. It’s much more than the newfound nimbleness, rapidity, and business opportunities it provides for digital disruptors creating services from people’s personal property (vehicles, dwellings), to new services in established verticals like finance, insurance, and healthcare.
The cloud’s greatest accomplishment is providing the architecture by which data management will boldly surge into the future to implement the foregoing—and countless additional—use cases.